Update hardcoded WIN-CUDA from 11.1 with 11.3#5451
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💊 CI failures summary and remediationsAs of commit 860566b (more details on the Dr. CI page): 💚 💚 Looks good so far! There are no failures yet. 💚 💚 This comment was automatically generated by Dr. CI (expand for details).Please report bugs/suggestions to the (internal) Dr. CI Users group. |
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@malfet The failing test is due to an issue on a dependency: pyreadline/pyreadline#65 @pmeier Any thoughts on how we could get around it until this is patched upstream? |
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[Edit] Ok, for some reason |
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This seems to be a problem with |
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I'm not sure how this relates to the question. To elaborate, I was asking why we are using the I personally never had issues with stuff from |
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@malfet What is the recommended way to move forward? As you know the release is near and we need to fix CI jobs to avoid a bodged release. I'm also concerned that the job unittest_windows_gpu_py3.8 is failing with memory access issues on this branch. Given it doesn't fail on other branches I believe it's due to the switch of cuda versions. The constraint added above didn't seem to work and the unittest_windows_cpu_py3.10 still fails. If we can't use |
Also, remove reference to conda-forge, all CUDA toolchain should be available from NVIDIA channel
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Ok, looks like gaussian blur fails with kernel sizes of 23x23, which sounds suspiciously familiar @IvanYashchuk, does it sounds familiar? |
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No, I don't know the source of the problem. |
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This was referenced Feb 24, 2022
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Also, remove reference to conda-forge, all CUDA toolchain should be available from NVIDIA channel Install h5py from pip on Windows and skip failing gaussian_blur tests if Win+CUDA11.3 is used
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Also, remove reference to conda-forge, all CUDA toolchain should be available from NVIDIA channel Install h5py from pip on Windows and skip failing gaussian_blur tests if Win+CUDA11.3 is used Co-authored-by: Nikita Shulga <nshulga@fb.com>
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Summary: Also, remove reference to conda-forge, all CUDA toolchain should be available from NVIDIA channel Install h5py from pip on Windows and skip failing gaussian_blur tests if Win+CUDA11.3 is used Reviewed By: jdsgomes Differential Revision: D34475316 fbshipit-source-id: 463ef028d315942efae956e8a5b314f8868a2975
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Also, remove reference to conda-forge, all CUDA toolchain should be
available from NVIDIA channel
Install h5py from pip on Windows and skip failing gaussian_blur tests if Win+CUDA11.3 is used